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多配送中心车辆调度问题的模型及其遗传算法研究 Abstract Inrecentyears,theproblemofvehicleschedulinginmultipledistributioncentershasreceivedincreasingattentionduetoitssignificantimpactonsupplychainmanagement.Inthispaper,amathematicalmodelforthemultipledistributioncentervehicleschedulingproblemisproposed,andageneticalgorithmisdesignedtosolveit.Theproposedgeneticalgorithmwascomparedwiththetraditionalheuristicalgorithm,andtheresultsshowedthattheproposedalgorithmoutperformedtheheuristicalgorithmintermsofthequalityofthesolutionandthecomputationtime. Introduction Thevehicleschedulingprobleminmultipledistributioncentersisacriticalissueinsupplychainmanagementandhasattractedsignificantattentionfromresearchersinrecentyears.Efficientandeffectivevehicleschedulingcanreducetransportationcosts,improvetheutilizationofresources,andenhancethelevelofcustomerservice.Thevehicleschedulingproblem,whichinvolvesmatchingvehiclestocustomers,hasbeenstudiedusingdifferentmathematicalmodelsandalgorithmictechniques.Asaresult,variousheuristicandmeta-heuristicalgorithmshavebeendevelopedforthisproblem. Inthispaper,weproposeamathematicalmodelforthemultipledistributioncentervehicleschedulingproblemanddesignageneticalgorithmtosolveit.Theproposedgeneticalgorithmiscomparedwiththetraditionalheuristicalgorithm,andtheresultsarepresentedandanalyzed.Theremainderofthepaperisorganizedasfollows;Section2providesaliteraturereviewofthevehicleschedulingproblem,whileSection3proposesthemathematicalmodelandthegeneticalgorithm.Section4presentstheresultsoftheexperimentsandtheanalysisofthecomputationalperformance.Finally,Section5concludesthepaperandsuggestsfutureresearchdirections. LiteratureReview Thevehicleschedulingprobleminmultipledistributioncentershasreceivedconsiderableattentionfromresearchersinrecentyears.Theprobleminvolvesmatchingvehiclestocustomersindifferentdistributioncenterstominimizetransportationcostswhilehonoringtheconstraintsthatariseinthedistributionsystem.TheproblemisknowntobeNP-hard,whichmeansthatitcannotbesolvedusingexactalgor